\begin{answer}
    \begin{enumerate}
\item Unsupervised EM takes over 150 iterations to converge, while semi-supervised EM takes over 20 iterations to converge.
\item For unsupervised EM, the clusters change for every random initialization. While for semi-supervised EM, the results are the same.
\item As shown in the figure, unsupervised EM takes two Gaussian to have high-variance, which is wrong. This is probably because high-variance will introduce more noise points. While for semi-supervised Gaussian, the results are quite accurate, with only one Gaussian that has high-variance.
    \end{enumerate}
 \end{answer}
